Teaser Image


Manually tuning physics-based animation parameters to explore a simulation outcome space or achieve desired motion outcomes can be notoriously tedious. Unfortunately, this problem has motivated many sophisticated and specialized optimization-based methods for fine-grained (keyframe) control, each of which are typically limited to specific animation phenomena, usually complicated, and, unfortunately, not widely used. In this paper, we propose Unified Many-Worlds Browsing (UMWB), a practical method for sample-level control and exploration of arbitrary physics-based animations. Our approach supports browsing of large simulation ensembles of arbitrary animation phenomena by using a unified volumetric WorldPack representation based on spatiotemporally compressed voxel data associated with geometric occupancy and other low-fidelity animation state. Beyond memory reduction, the WorldPack representation also enables unified query support for interactive browsing: it provides fast evaluation of approximate spatiotemporal queries, such as occupancy tests that find ensemble samples (“worlds”) where material is either IN or NOT IN a user-specified spacetime region. The WorldPack representation also supports real-time hardware-accelerated voxel rendering by exploiting the spatially hierarchical and temporal RLE raster data structure to accelerate GPU ray tracing of compressed animations. Our UMWB implementation supports interactive browsing (and offline refinement) of ensembles containing thousands of simulation samples, and fast spatiotemporal queries and ranking. We show UMWB results using a wide variety of different physics-based animation phenomena---not just Jell-O.




Purvi Goel and Doug L. James. 2022. Unified Many-Worlds Browsing of Arbitrary Physics-based Animations. ACM Trans. Graph. 41, 4, Article 156 (July 2022), 15 pages.


We thank the anonymous reviewers for constructive feedback; Kangrui Xue and Sophie Wyetzner for proof reading; Christopher Twigg for MWB-era discussions on fluid browsing. We thank SideFX for donating Houdini licenses which were helpful in producing examples and renders. We thank Gianluca Iaccarino, Javier Urzay, and other Stanford INSIEME group members for project feedback. This material is based upon work supported by the Department of Energy, National Nuclear Security Administration under Award Number DE-NA0003968.